Retrieval of Atmospheric CO2 and CH4 Variations Using Ground ...

Hindawi Publishing Corporation Journal of Spectroscopy Volume 2015, Article ID 736382, 9 pages http://dx.doi.org/10.1155/2015/736382

Research Article Retrieval of Atmospheric CO2 and CH4 Variations Using Ground-Based High Resolution Fourier Transform Infrared Spectra Tian Yuan,1 Liu Cheng,1,2 Sun You Wen,1 Xie Pin Hua,1,2 Wang Wei,1 Liu Wen Qing,1,2 Liu Jian Guo,1,2 Li Ang,1 Hu Ren Zhi,1 and Zeng Yi1 1

Key Lab of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China 2 University of Science and Technology of China, Hefei 230026, China Correspondence should be addressed to Liu Cheng; [email protected] Received 23 June 2015; Accepted 31 August 2015 Academic Editor: Arnaud Cuisset Copyright © 2015 Tian Yuan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. High resolution Fourier transform near IR solar spectra are used to estimate the column-averaged dry-air mole fraction (DMF) of CO2 and CH4 variations in the atmosphere. The preliminary retrieval results for CO2 and CH4 variations in the area of Hefei, China, are presented, and the underlying error sources are also analyzed. Both a forward analysis and an inversion algorithm are included in the retrieval. The forward analysis uses the modeled atmospheric transmittance to line-by-line (LBL) convolute the instrument line shape function. The influences of the temperature, pressure, humidity, and a priori gases are considered in the atmospheric transmittance model. The inversion algorithm is based on the nonlinear iterative and nonlinear least squares spectral fitting, which is used to obtain VCDCO2 and VCDCH4 (which represent vertical column density of CO2 and CH4 , resp.). Furthermore, the VCDO2 is also retrieved for converting the VCDs into DMFs. DMFs are final products of data analysis. The inversion results can clearly resolve the tiny variations of CO2 and CH4 under strong atmospheric background. Spectral fitting residuals for both VCDCO2 and VCDCH4 are less than 0.5%. Finally, CO2 and CH4 diurnal variations are investigated based on a typical observation. About 2 ppm amplitude for DMFCO2 diurnal variations and less than 15 ppb amplitude for DMFCH4 are observed.

1. Introduction Greenhouse effect caused by greenhouse gases (GHGs) can produce a series of environmental and economic problems. Recording GHG variations with high precision and accuracy is of great significance for predicting future climate change. Besides, good knowledge of global source and sink of carbon is the prerequisite for global warming control because carbon (except vapor) is the most important component in the GHGs [1]. CO2 and CH4 are two important GHGs and carbon compounds, which have been the research hotspots for decades [1, 2]. To have good knowledge of these two gases, the world has established more than 100 in situ observation sites over the past 30 years [3, 4]. A large number of GHG researches have been accomplished based on the combination

of the in situ observation and global transmission model. In situ observations are mainly focused on the atmospheric boundary layer. The most striking characteristic of in situ observations on the atmospheric boundary layer is its high accuracy. But it is severely affected by the local source and sink and limited in the spatial coverage range [5]. Column density measurements can fill these gaps and are less influenced by the atmospheric boundary layer height changes and vertical transport [6]. Compared to in situ observation, column density measurements are less affected by temporal and spatial variations and thus make the horizontal gradients of the results more directly related to the underlying regionalscale fluxes [5]. The typical high precision tools for column measurements are satellite-based and ground-based Fourier transform spectrometer [7]. Currently, satellite-based Fourier transform spectrometer includes GOSAT (Japan), launched

2

Journal of Spectroscopy

Aperture 𝜙 = 25 cm

Solar tracker

(a) Indoor

(b) Outdoor

Figure 1: Experimental instrument system.

in 2009, and the OCO-2 (United States), launched in 2014. To validate these satellite data, ground-based atmospheric GHGs observation network is established, called the Total Carbon Column Observation Network (TCCON) [5]. However, there is still no TCCON site locating in the area of China. That means it is unable to validate the satellite-based measurements in the whole area of China. This paper aims to first retrieve CO2 and CH4 variations in China using ground-based high resolution Fourier transform infrared spectra. This study can not only provide an evidence for resolving the local source and sink of carbon circle but also facilitate the satellite-based GHG measurements validation.

2. Instrument Descriptions The observation laboratory is installed on an island located in the west of Hefei (the capital of Anhui Province) in central and eastern China. It is adjacent to a lake with a longitude of 117∘ 10󸀠 E, latitude of 31∘ 54󸀠 N, and altitude of 30 m. The system consists of a high resolution ground-based Fourier transform infrared spectrometer (IFS125HR) and a solar tracker (Tracker-A Solar 547), both of which are purchased from Bruker Company. IFS125HR has 9 scanner compartments, with a maximum resolution of 0.00096 cm−1 , and covers a spectral range of 5∼50,000 cm−1 . The solar tracker is mounted inside a dome controlled by a motor on the building roof (as shown in pictures on the right of Figure 1). A tracking precision of ±0.1∘ can be achieved by using the Camtracker mode (a built-in camera continuously adjusts the distance

between the sun spot and the field spot). Solar tracker directs the sun light through the roof aperture (as shown in pictures on the left of Figure 1) into the spectrometer. For CO2 and CH4 observation, the spectral resolution is set to 0.02 cm−1 and the CaF2 beam splitter is used [8]. We choose InSb as the detector which covers 3900∼15500 cm−1 spectral range and cooled with liquid nitrogen during operation. In order to avoid detector saturation, we select a minimum entrance aperture (0.5 mm) and insert an attenuator (grid metal) in front of the detector.

3. Spectra Retrieval Spectra retrieval includes two steps, that is, VCDs retrieval and then DMFs retrieval. We use the GFIT algorithm to retrieve the CO2 and CH4 VCDs. GFIT is developed by JPL (Jet Propulsion Laboratory), California Institute of Technology [5, 9]. It combines nonlinear iteration and nonlinear least squares fitting. It is a standard inversion algorithm for TCCON network. When fitting a spectral range, GFIT attempts to minimize the quantity 𝜒2 with respect to the variables 𝛼, 𝛽, 𝛿, 𝑥1 , 𝑥2 , and 𝑥3 and other parameters: 2

𝑁𝑀 (𝑌𝑀 𝑖

𝜒 = ∑ 𝑖=1

− 𝑌𝐶 (𝛼, 𝛽, 𝑉𝑖 + 𝛿, 𝑥1 , 𝑥2 , 𝑥3 ⋅ ⋅ ⋅ )) 𝛿𝑖2

2

,

(1)

where 𝑌𝑀 represents the measured spectra, 𝑌𝐶 represents the calculated spectra, 𝛼 is termed the continuum level, 𝛽 is termed the continuum tilt, 𝛿 is the frequency shift, and the

3

Residual (%)

Journal of Spectroscopy hf141008_0042NIRsolar.0009 55.011 0.2459

2.0 1.0 0.0 −1.0 −2.0 1.0

Transmittance

0.8 0.6 0.4 0.2 0.0

6300.0

6310.0

6320.0

Tm Tc CO2 H2 O

6330.0

6340.0

6350.0

Frequency (cm−1 )

6360.0

6370.0

6380.0

HDO Other Solar

Figure 2: CO2 spectral fitting within 6339 cm−1 window: the spectrum was recorded on October 8, 2014, 0:47 (UTC). Black lines are the measurements, orange lines are the fitted transmittance, and contributions from individual gases are shown in color. Fitting residuals (𝑇𝑚 −𝑇𝑐 ) for CO2 are 0.2459%.

various 𝑥 terms are the scale factors for the different gases and 𝜎𝑖 is the uncertainty in the value of the 𝑖th element of 𝑌𝑀. 𝛼, 𝛽, 𝛿, 𝑥1 , 𝑥2 , 𝑥3 , . . ., and so forth are important outputs of GFIT. Due to the complexity of modeling the measured spectra 𝑌𝑀, a forward model 𝑌𝐶 is exploited. It is expressed as 𝑌𝑀 = 𝑌𝐶 + 𝜀,

(2)

where 𝜀 is the measurement error. Forward model 𝑌𝐶 is commonly termed the convolution of atmospheric transmittance and the instrument line shape function [10, 11]: 𝑦𝑖𝑐 = {[𝐶 + 𝑆 (]𝑖 − ]0 )] 𝑦𝑖top ILS (]𝑖 , 𝛿) ⊗ 𝑇 (]𝑖 )} + 𝑧offset , 70

𝐾

𝐿

𝑇 (]𝑖 ) = 𝑒− ∑𝑗=0 ∑𝑘 ∑𝑙 {[𝑐𝑘 𝑤0𝑘,𝑗 ][𝑅𝑙,𝑘,𝑗 𝐹𝑙,𝑘,𝑗 (]𝑖 −]𝑘,𝑗 )]𝑛𝑗 𝑠𝑗 } ,

(3) (4)

where 𝑦𝑖𝑐 is the 𝑖th element of 𝑌𝐶, 𝑦𝑖top is the atmosphere top layer spectra, 𝐶 is continuum level, 𝑆 is continuum tilt, 𝛿 is frequency drift, and 𝑇(]𝑖 ) represents atmospheric transmittance. When modeling measured spectra, a discrete, line-by-line, multilayer, and multispecies expression for the atmospheric transmittance is applied as expressed by (4) [5]. ]0 is the center frequency of a spectral window, ILS(]𝑖 , 𝛿) is instrument line shape function, and 𝑧offset is spectral zero level offset. And the ILS used in GFIT is a nominal ideal ILS that is a numerical convolution of the sinc function with a rectangular function when the instrument is well aligned. The effect of the thermal radiation is ignored due to its negligible influence on the near-infrared spectrum.

Solar intensity relative fluctuation threshold is set to 5% for removing the interference of clouds and aerosols. 3.1. Model Parameters Determination. In order to achieve high precision retrieval, longitude, latitude, altitude, a priori profiles, real-time surface temperature, humidity, pressure, wind speed, wind direction, and other meteorological parameters need to be considered in the process of the forward model calculation [12]. In addition, the high resolution spectrometer IFS125HR should be calibrated by a low pressure HCl cell regularly because instrument alignment has great influence on the inversion results [10]. For the current version of spectra, we did not save the real-time surface temperature, humidity, and pressure parameters, and no HCl cell is available. Thus, in this study, we have to make some assumptions in the model calculation. (1) Inside the laboratory, the air conditioning is set to a constant value of 24∘ , the dehumidifier is set to a constant value of 60%, and the IFS125HR is evacuated while saving the solar spectra. So we assume that the temperature inside the instrument (𝑇inside ) is a constant value of 24∘ , the internal pressure (𝑃inside ) is a constant value of 1 mbar, the internal relative humidity (𝐻inside ) is a constant value of 60%, the temperature outside the instrument (𝑇outside ) is a constant value of 24∘ , the external pressure (𝑃outside ) is a constant value of 1 standard atmospheric pressure (1024 pa), and the external relative humidity (𝐻outside ) is a constant value of 60%. In addition, a priori profiles for temperature, pressure, and humidity above observation station are based on NCEP (National Center for Environmental Prediction) data [13]. A priori profiles for all gases use the American standard

Journal of Spectroscopy Residual (%)

4 hf141008_0042NIRsolar.0006 54.394 0.3535

2.0 1.0 0.0 −1.0 −2.0 1.0

Transmittance

0.8 0.6 0.4 0.2 0.0 5880.0

5900.0

Tm Tc CH4 CO2

5920.0 5940.0 Frequency (cm−1 )

5960.0

5980.0

H2 O N2 O Other Solar

Figure 3: CH4 spectral fitting within 5938 cm−1 window: the spectrum was recorded on October 8, 2014, 0:47 (UTC). Black lines are the measurements, orange lines are the fitted transmittance, and contributions from individual gases are shown in color. Fitting residuals (𝑇𝑚 −𝑇𝑐 ) for CH4 are 0.3535%.

atmospheric parameters for the mid-latitude of northern hemisphere. (2) We already aligned the IFS125HR just before we started to save the spectra, so we assume that the alignment of instrument is well because of the excellent stability of the instrument; that is, the influence of the instrument drift is neglected for all the spectra. (3) Time correction is done every day before observations, so the saved spectra are consistent with the UTC (Universal Time Coordinated) within ±1-second precision. 3.2. VCD Retrieval. We use the GFIT algorithm to calculate the CO2 and CH4 VCDs which finds the best fitting between the calculated spectra and the measured spectra [14]. The most important outputs of the GFIT algorithm are scaling factors and their uncertainties as mentioned in (1). A priori profile mole fraction of a gas is multiplied by the scaling factor to yield the retrieved vertical column density [13] ∞

apriori 𝑛 𝑑𝑧, columngas = SFgas ∫ 𝑓gas 𝑧𝑠

(5)

apriori where SFgas is the scaling factor for a gas, 𝑓gas is the a priori profile of the gas, 𝑛 is the total molecules number, 𝑧 represents altitude, and 𝑧𝑠 is the altitude of the first mirror of the solar tracker.

3.3. DMF Calculation. Gas column average dry-air mole fraction (DMF) is defined as 𝑋gas =

columngas total dry column

.

(6)

Because VCDO2 in the atmosphere is well known, the total dry-air column can be obtained by using the relationship between VCDO2 and the total dry-air column [15]: total dry column =

columnO2 0.2095

.

(7)

Substituting (7) into (6) yields the DMF: 𝑋gas = 0.2095

columngas columnO2

.

(8)

The advantages of DMF compared with VCD are as follows: (1) reducing the influence of surface pressure changes and water vapor interference on the inversion results; (2) reducing the systematic error sources which affect both the target gas and O2 ; (3) improving the inversion precision by minimizing the common scatter [15].

4. Data Analysis and Discussion In this study, the direct solar spectra collected between October 6, 2014, and December 1, 2014, are retrieved. All the spectra which are saturated or the signal to noise ratios (SNR) which are less than 500 or the relative intensity variations which are larger than 5% (mainly caused by clouds and/or aerosols) are removed. CO2 , CH4 , and O2 gases are retrieved simultaneously. Retrieval window parameters for CO2 , CH4 , and O2 are listed in Table 1. The two central frequencies for CO2 windows are 6220.00 cm−1 and 6339.50 cm−1 , respectively. The final VCDCO2 is the average of the windows’ results. The same treatment is also applied to CH4 . The target gases

5

Residual (%)

Journal of Spectroscopy hf141008_0042NIRsolar.0009 55.011 0.3085

2.0 1.0 0.0 −1.0 −2.0 1.0

Transmittance

0.8 0.6 0.4 0.2 0.0

7800.0

7850.0

Tm Tc O2 0O2 H2 O

7900.0

7950.0

Frequency (cm−1 )

8000.0

HF CO2 Other Solar

CO2 _error (%)

Figure 4: O2 spectral fitting within 7885 cm−1 window: the spectrum was recorded on October 8, 2014, 0:47 (UTC). Black lines are the measurements, orange lines are the fitted transmittance, and contributions from individual gases are shown in color. Fitting residuals (𝑇𝑚 −𝑇𝑐 ) for O2 are 0.3085%. 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4

Hefei CO2 _error (%) versus time

10/08

10/13

10/18

10/23

10/28

11/02

11/07

11/12

11/17

11/22

11/12

11/17

11/22

Hefei CO2 (molecules /cm2 ) versus time

9.0 1e21

CO2

8.8 8.6 8.4 8.2 8.0

10/08

10/13

10/18

10/23

10/28 11/02 Time

11/07

Figure 5: VCDCO2 time series ranging from October 6, 2014, to December 1, 2014, which are the average of the retrieval values in 6220 cm−1 and 6339 cm−1 windows.

of interest (bold font) and interfering gases are also shown in Table 1. We set a fitting residual of